• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.108-120
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• 2008

This paper discusses the prediction of deforestation areas using probability models from forest census database, Geographic information system (GIS) database and the land cover database. The land cover data was analyzed using remotely-sensed (RS) data of the Landsat TM data from 1989 to 2001. Over the analysis period of 12 years, the deforestation area was about 40ha. Most of the deforestation areas were attributable to road construction and residential development activities. About 80% of the deforestation areas for residential development were found within 100m of the road network. More than 20% of the deforestation areas for forest road construction were within 100m of the road network. Geographic factors and vegetation change detection (VCD) factors were used in probability models to construct deforestation occurrence map. We examined the size effect of area partition as training area and validation area for the probability models. The Bayes model provided a better deforestation prediction rate than that of the regression model.

• Spatial Information Research
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• v.12 no.3
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• pp.285-298
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• 2004

Transportation digital map has built based on NGIS (national geography institute's 1 :5000 digital database) which derived from the aerial photo materials. Transportation digital map is a part of National Transportation Database Building Project carried out by the Korea Transport Institute and Ministry of Construction and Transportation. Transportation digital map for the purpose of transportation plan and investment has been updated and corrected the NGIS database especially for road network. Transportation digital map database is essential basic data fully applied for transportation policy and planning. The database must be reliable and objective to be applied for national transportation policy decision and transportation analysis. In addition, it needs accuracy and currentness to reflect the road network for the survey year. To satisfy the purpose of the database, following steps are necessary first, data Production and building has to be done by guideline of survey and database building. Secondly, geometric and logical errors which can occur during the survey and database building should be carefully detected. Thirdly, sectional guideline for database examination and procedure needs to be set up systematically and coherently This study is about examination guidelines for section and procedure on nodes and links which are essential object in transportation digital map database. According to the type of error, consistent and systematic error examination can lead to quality guarantee for objective and reliable database.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.26-32
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• 2008

A pedestrian navigation system, an information delivery server, and a program for naturally guiding (such as speech-guiding) the user of a portable terminal at an intersection. An information delivery server comprises a map database containing data such as nodes including paths constituting intersections, links, and costs of the links. The node-link structure is the most important part in pedestrian navigation system. Functional requirements for the road map database vary in different navigation phases. though there are various road network models, their traditional node-link structures, unfortunately, do not solve the problem well. This paper proposes a node-link structure for pedestrian navigation system. The network topological structure in pedestrianl network is presented, which accords with the practical walking habit better than traditional way treating the entire road network.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.121-125
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• 2007

Recently, constructing and complementing the road network database are a main key in all social operation in our life. However it needs high expenses for constructing and complementing the data, and relies on many people for finishing the tasks. This study propose a novel method to extract urban road networks from 3-D LiDAR data automatically. This method integrates height, reflectance, and clustered road point information. Geometric information of general roads is also applied to cluster road points group correctly. The proposed method has been tested on various urban areas which contain complicated road networks. The results conclude that the integration of height, reflectance, and geometric information worked reliably to cluster road points.

• Health Policy and Management
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• v.27 no.3
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• pp.229-240
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• 2017

Background: This study purposed to analyze the spatial accessibility of women in childbearing age to the healthcare organizations (HCOs) providing delivery services in Gangwon-do. Methods: Network analysis was applied to assess the spatial accessibility based on the travel time and road travel distance. Travel time and travel distance were measured between the location of HCOs and the centroid of the smallest administrative areas, eup, myeon, and dong in Gangwon-do. Korean Transport Database Center provided road network GIS (Geographic Information System) Database in 2015 and it was used to build the network dataset. Two types of network analysis, service area analysis and origin-destination (OD)-cost matrix analysis, applied to the created network dataset. Service area analysis defined all-accessible areas that are within a specified time, and OD-cost matrix analysis measured the least-cost paths from the HCOs to the centroids. The visualization of the number of the HCOs and the number of women in childbearing age on the Ganwon-do map and network analysis were performed with ArcGIS ver. 10.0 (ESRI, Redlands, CA, USA). Results: Twenty HCOs were providing delivery services in Gangwon-do in 2016. Over 50% of the women in childbearing age were aged more than 35 years. Service area analysis found that 89.56% of Gangwon-do area took less than 60 minutes to reach any types of HCOs. For tertiary hospitals, about 74.37% of Gangwon-do area took more than 60 minutes. Except Wonju-si and Hoengseong-gun, other regions took more than 60 minutes to reach the tertiary hospital. Especially, Goseong-gun, Donghae-si, Samcheok-si, Sokcho-si, Yanggu-gun, Cheorwon-gun, and Taebaek-si took more than 100 minutes to the tertiary hospital. Conclusion: This study provided that the accessibility toward the tertiary hospital was limited and it may cause problems in high-risk delivery patients such as over 35 years. Health policy makers will need to handle the obstetric accessibility issues in Gangwon-do.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.143-150
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• 2013

The purpose of this study is to suggest the methodology to develop variable-scale network model, which is able to induce large-scale road network in detailed level corresponding to small-scale linear objects with various abstraction in higher level. For this purpose, the definition of terms, the benefits and the specific procedures related with a variable-scale model were examined. Second, representation level and the components of layer to design the variable-scale map were presented. In addition, rule-based data generating method and indexing structure for higher LoD were defined. Finally, the implementation and verification of the model were performed to road network in study area (Jeju -do) so that the proposed algorithm can be practical. That is, generated variable scale road network were saved and managed in spatial database (Oracle Spatial) and performance analysis were carried out for the effectiveness and feasibility of the model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.34-42
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• 2014

This study is a fundamental research to determine the emergency evacuation roads considering road network function and connectivity. First of all, the functional aspects of the road networks are analyzed in the target area, Sejong city, by using degree centrality(DC) and closeness centrality(CC) from GIS based database. Secondly, how network connectivity makes a change in user's travel pattern and travel time and how it affects the whole network are analyzed using TransCAD simulation program. Finally, after performing cluster analysis of index, first and second emergency evacuation roads are determined by judging the characteristics of clusters. The results of this research will be helpful for making a decision to diminish secondary damages when confronting unexpected disasters.

• Journal of IKEEE
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• v.11 no.4
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• pp.348-357
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• 2007

Due to the improved performance and cost of personal mobile devices and rapid progress of wireless communication technology, the number of users who utilize these devices is increasing. This trend requires various types of services be available to users. So far, there have been many solutions provided for the shortest path problem. But, technologies which can offer various recommendation services to user depending on user’s current location are focused on Euclidean spaces rather than road network. Thus, in this paper, we extend the previous work to satisfy this requirement on road network database. Our proposed scheme requires pre-computation for the efficient query processing. In the preprocessing step, we first partition the input road network into a fixed number of Voronoi polygons and then pre-compute routing information for each polygon. In the meantime, we select the number of Voronoi polygons in proposition to the scale of road network. Through this selection, the required size of pre-computation is linearly increasing to the size of road network. Using this pre-computated information, we can process queries more quickly. Through experiments, we have shown that our proposed scheme can achieve excellent performance in terms of scheduling time and the number of visited nodes.

• The Journal of Information Technology and Database
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• v.7 no.1
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• pp.42-53
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• 2000

The major goal of this research is to develop an optimal route search algorithm for an intelligent route guidance system, one sub-area of ITS. ITS stands for intelligent Transportation System. ITS offers a fundamental solution to various issues concerning transportation and it will eventually help comfortable and swift moves of drivers by receiving and transmitting information on humans, roads and automobiles. Genetic algorithm, and fuzzy logic are utilized in order to implement the proposed algorithm. Using genetic algorithm, the proposed algorithm searches shortest routes in terms of travel time in consideration of stochastic traffic volume, diverse turn constraints, etc. Then using fuzzy logic, it selects driver-preference optimal route among the candidate routes searched by GA, taking into account various driver's preferences such as difficulty degree of driving and surrounding scenery of road, etc. In order to evaluate this algorithm, a virtual road-traffic network DB with various road attributes is simulated, where the suggested algorithm promptly produces the best route for a driver with reference to his or her preferences.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.26-31
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• 2015

Success of the construction companies is based on the successful completion of projects within the agreed cost and time limits. Artificial neural networks (ANN) have recently attracted much attention because of their ability to solve the qualitative and quantitative problems faced in the construction industry. For the estimation of cost and duration different ANN models were developed. The database consists of data collected from completed projects. The same data is normalised and used as inputs and targets for developing ANN models. The models are trained, tested and validated using MATLAB R2013a Software. The results obtained are the ANN predicted outputs which are compared with the actual data, from which deviation is calculated. For this purpose, two successfully completed highway road projects are considered. The Nftool (Neural network fitting tool) and Nntool (Neural network/ Data Manager) approaches are used in this study. Using Nftool with trainlm as training function and Nntool with trainbr as the training function, both the Projects A and B have been carried out. Statistical analysis is carried out for the developed models. The application of neural networks when forming a preliminary estimate, would reduce the time and cost of data processing. It helps the contractor to take the decision much easier.